Tactical Network Planning for

Food Aid Distribution in Kenya M.-È. Rancourt, J.-F. Cordeau, G. Laporte and B. Watkins, Computers &

Operations Research, 56: 68-83, 2015

Transportation Center Seminar Northwestern’s McCormick School of Engineering and Applied Science March 5, 2015

Marie-Ève Rancourt, Ph.D. Department of Management and Technology, ESG UQÀM

Outline

Context: humanitarian logistics

The network design problem

Field work and data collection

Mathematical formulation

Results

Conclusions and future research directions

Humanitarian logistics

The process of planning, implementing and

controlling the efficient, cost-effective flow and

storage of goods and materials, as well as related

information, from the point of origin to the point of consumption for the purpose of meeting the end

beneficiaries’ requirements

A. Thomas and M. Mizushima (2011)

Humanitarian logistics Disaster response versus development projects

Disaster

response

The Federal Emergency

Management Agency

(FEMA) defines a

disaster as:

« an event that causes

100 deaths or 100

human injuries or

damage worth 1 million

dollars »

Development

projects

Also involve human

suffering and

economic damage,

but covering longer

time-spans

Their cause can usually

not be traced back to

a specific catastrophic

event

East Africa struggles with…

Extreme poverty and rapid population growth

Wars and population migrations

Diseases (malaria, HIV/AIDS, …)

Gender issues and lack of education

Governance challenges

Fragile food production systems

Recurrent droughts and floods

Food insecurity

Food insecurity

Hunger and malnutrition are the greatest risks to global health (World Food Programme, UN)

Eradicating extreme poverty and hunger is the first goal of the eight UN Millennium Development Goals

Sub-Saharan Africa is the only region in the world suffering from persistent chronic food insecurity

Source: FEWS NET

Acute food

insecurity as of

today

Food aid as an instrument to reduce food

insecurity

Kenya

Between 1988 and 2011

182,000 MT per year on average (FAO)

Number of beneficiaries

14.3 million people in 2013-2014

Main causes

Poverty

Seasonal droughts

Refugee camps (about 480,000 refugees in Dadaab and Kakuma)

Food aid

Providing food and related assistance to tackle hunger,

either in emergency

situations, or to help with

deeper, longer term hunger alleviation and achieve food

security

This project focuses on in-

kind food donations to beneficiaries

Objective of this project

Objective: Improve the design of the food aid

distribution network taking into account the welfare of

multiple stakeholders

Scope: Determination of final delivery points, last-mile of

food aid distribution

Methodology: Mathematical programming

Problem class: Facility location and coverage problems

Geographical coverage: Garissa district, Kenya

Collaboration

The World Food Programme (WFP) of the United

Nations

The largest humanitarian agency, aims to fight against

hunger in the world

Know-how in the areas of food security analyses, nutrition,

food procurement and logistics (transportation and

warehousing)

Kenya Red Cross

Run different projects (services): famine, education, blood,

first aid, disaster and emergency

Scientific contributions

The main challenge of the project lies more in

modeling the problem, carrying out data collection

and processing, and performing analyses than on

algorithmic development

Describe the logistics processes of food aid distribution

and estimate stakeholders’ costs

First paper to apply optimization tools using real data in

the context of last-mile food aid distribution in Africa and

computing stakeholders’ tradeoff costs

Steps

1. Understand the food distribution process

2. Determine the network parameters Demand

Potential FDP locations

Distances

3. Estimate the stakeholder cost functions Beneficiaries

World Food Programme (WFP)

Kenya Red Cross

4. Formulate and solve the mathematical models

5. Estimate tradeoffs

Step 1: Understanding the food distribution process

Field work

Interviews

Facility visits

Food distribution observation

Food distribution process

Hub

Legend:

EDP

FDP

Food entries

(international

transport)

Extended Delivery Point

(EDP)

Final Delivery Point (FDP)

Secondary

transport

Primary

transport

Food aid regional supply chain Operations and stakeholders

Secondary

transport FDPs

WFP & Red-Cross Red-Cross &

Community

This project!

Beneficiaries

Operations

Stakeholders

Food aid Hand-out

(distribution) EDP Garissa

Garissa and its surroundings

Why Garissa and its surroundings?

One of the most vulnerable regions in Kenya

35% of the region’s population received food aid in

the last 12 years (62% during the most difficult period)

High poverty rate

Arid land with low rainfall

Pastoralism is the dominant livelihood system

Food aid is constant

Fixed distribution system which justifies the need for an

optimized network

EDP:

Red Cross is responsible for the

reception and storage of food

Red Cross organizes

secondary transport

operations, but the WFP bears

the transportation costs

FDP et la community

Facilitators:

“Food relief committee” chairman

Red Cross monitor

Spread settlements

Poor infrastructures!

18

Activities/Responsibilities at the EDP and a FDPs

“Community Relief Committee”

Elected by the community

Trained by Red Cross

Targeting, record keeping, arrange food distribution, provide storage and ensure security

Red Cross

Ensure that food assistance reaches beneficiaries

Assist the community

Activities/Responsibilities at a FDP

Food aid:

Vegetable oil

Sorghum (cereal)

Unloading

Truck arrival

Records: Beneficiary book

Distribution book

Activities/Responsibilities at a FDP

Activities/Responsibilities at a FDP

21

Shipment management Counting

Signing waybill

Losses/damaged bags

Activities at a FDP

Distribution “Scooping”

Hand-out (distribution)

Donkey transportation

service

Tactical “FDP” location problem

F

D

P

F

D

P

F

D

P

F

D

P

F

D

P

FD

P

F

D

P

F

D

P

Garissa

EDP F

D

P

Population points (V1)

Potential FDP locations (V2)

Transportation costs

(WFP)

Location and hand-out costs

(Kenya Red Cross)

Access costs (beneficiary

opportunity costs)

Costs:

Nodes:

Step 2: Determine the physical network structure

1. Demand

Population needs

Population locations

2. Potential FDP locations

3. Transportation network (distances)

Distance from each population point to closest road

Distance from Garissa EDP to each potential FDP

locations

Distance from each population points to each

potential FDP locations

Question 1 – Demand

Where are the beneficiaries?

Geographic Information Systems (GIS) and gridded

population data

How much food are they entitled to?

2012 Short Rain Need Assessment

Long rains Short rains Long dry Long

rains

Short dry

Need assessment: Determination of the demand for

the following 6 months.

Need assessment in Kenya

Need assessment in Kenya

For each division of Kenya, two parameters are

determined (effective for a period of 6 months):

Number of beneficiaries

Ration entitlement

Kenya

Locations (2,427)

Sub-locations

(6,612)

(# beneficiaries, ration entitlement)

Garissa

Districts (46 -- 16 to 26 )

Provinces (8)

Divisions (497)

400g of cereal flour/rice/bulgur

60g of pulses

25 g of oil (vit. A fortified)

50 g of fortified blended foods (Corn Soya

Blend)

15g of sugar

15g of iodized salt

Food basket

2012 Short Rain Assessment for Garissa and

its surroundings

Food aid requirement (tonnes/month)

Set of population points − V1 Source: GIS gridded population data

1 km

0 0 3 3 3

3 3

3

5 5 5 5

0 0 3 3 3 3

0 0 0 0 2 2

3 3 5 5 10

1

2

5 5

10

1

2

10

1

2

10

1

2 36

4

3

65

7

1 95

8

9

65

7

1

1

6

3

5

1 km

1 km

1 km

Needs qi at population point i :

With pi the population at i, B the number of beneficiaries,

P the total population and ration the entitled amount of

food aid per beneficiary at smallest division level

V1

qi =pi

PB × ration

Question 2 – Potential FDP locations

Where are the potential FDP locations?

Geographic Information Systems (GIS)

Road network

Population data

Set of potential FDP locations – V2 Sources: GIS gridded population data and road vectors

1 km

0 0 3 3 3

3 3

3

5 5 5 5

0 0 3 3 3 3

0 0 0 0 2 2

3 3 5 5 10

1

2

5 5

10

1

2

1

0

1

2

10

1

2 36

4

3

65

7

1 95

8

9

6

5

7

1

1

6

3

5

1 km

1 km

1 km

FDP • Close to a road (≤ 200 m)

• Population center (≥ 20 people)

V2 F

D

P

FDP

FDP

FDP

FDP

FDP

FDP

FDP

FDP

FDP

Question 3 – Transportation distances

What are the network transportation distances?

Geographic Information Systems (GIS)

Road network

Population data

Algorithms

Distances within the network

Garissa EDP to each

potential FDP

Road distances

Source: Google maps API

1460 distances

Each population point to each potential FDP

Geographical distances

Source: GIS

35,701,380 distances

3 3 3

3 3

3

5 5 5 5

3 3 3 3

2 2

3 3 5 5 10

1

2

5 5

10

1

2

10

1

2

10

1

2 36

4

3

65

7

1 95

8

9

65

7

1

1

6

3

5

FDP

FDP

FDP

FDP

FDP

FDP FDP

FDP FDP

Garissa

EDP

…

Network description

Step 3: Estimate the stakeholder costs

Stakeholders that bear costs

Beneficiary opportunity costs (access costs)

WFP (transportation costs)

Kenya Red Cross (location and hand-out costs)

Data sources

Beneficiary questionnaires

Contracts between the WFP and the Kenya Red

Cross

Beneficiary opportunity costs

Value of walking time:

0.25 h/km · 2 · distance to FDP (km) · 22,25 KSh/h

Value of food transport service (donkey):

20 KSh + 2.5 KSh/km · distance to FDP (km)

Beneficiary opportunity costs:

11,4 KSh/km · distance to FDP (dij) + 20 KSh

Minimum wage rate for unskilled labor Walking time (pace: 4 km/h)

Statistics based on a monitoring report for WFP

Transportation costs (WFP)

The Red Cross contracts and coordinates with local

transporters, but WFP fixes secondary transportation rates

and pays for the services:

Transportation costs to serve the FDPs depend on the

distance and the quantity of food delivered

F

D

P

Garissa

EDP

F

D

P

F

D

P

0 Q1

Q1

2 Q2

3 Q3

:

: ,

Q2

Q3

Location and hand-out costs

(Kenya Red Cross)

Fixed costs: Relief comity training and registration

validation

Two workdays for the Red Cross facilitator

Variable costs: Monthly food distribution

monitoring

Two workdays per month for the Red Cross staff

(announcement, dispatch and distribution)

Total estimated costs: KSh

Step 4: Mathematical formulation of the problem

Define the decision variables

Determine the objective function

Formulate the constraints

Decision variables and coverage

radius

Decision variables

Radius of coverage r and Wi(r)

F

D

P

F

D

P

F

D

P

Wi(r)

F

D

P

dij < r

d

ij > r

dij < r

dij < r

xij

xij

xij

V1(r)

≠ Ø

Mathematical formulation –

Cost Model

Beneficiaries opportunity

costs

Transportation costs

(WFP)

Location and hand-out costs

(Kenya Red Cross)

Open FDPs

Demand

Binary

Non negativity

Step 5: Computational results

Solve the problem using the CPLEX 12.5 library

in a C++ program Optimality gap: 0.1%

Comparative analyses

Impact of the response system structure on the

stakeholder welfare costs

Compare results of the cost model with classic covering models

Solution illustrations

Solution characteristics

% of the population covered as a function of r

Average walking time per beneficiary as a function of r

Covered people as a function

of the coverage radius

Uncovered people as a

function of the coverage

radius

% of the population uncovered as a function of r

Average walking time per beneficiary as a function of r

Assuming they register to the

closest open FDP

Stakeholder costs

Red Cross

5% of the total

cost on

average

Beneficiaries

22% of the total

cost on average

WFP

73% of the total

cost on average

Total welfare

cost

Stakeholder costs per beneficiary

Fair radius

Fair and cost-

efficient solutions obtained with:

r = 10, 11, … , 17.

Fair?

Complying with The

Sphere Project

Standards (2014), i.e.

90% of the

beneficiaries should

be covered within a

one-day return walk .

Here, about 92% of

the people are

covered with an

average walking time

of 2 hours.

Tradeoff between beneficiary and

transportation costs

Minimizing beneficiary

opportunity costs

Average % of decrease in

average walking time per

beneficiary

37%

Average % of increase in

transportation costs

14%

Minimizing supply transportation costs (WFP)

Average % of decrease in

transportation costs

15%

Average % of increase in

beneficiary average walking time

188%

A small increase in WFP costs can yield a large

reduction in beneficiary opportunity costs

Coverage Model

Maximize covered need with 156 FDPs

Comparative analysis – Coverage

Comparison of the % of covered people obtained with the cost model and the coverage model with 156 FDPs

Less covered people when r ≤ 10

Comparative analysis – Stakeholder

costs

Larger beneficiary and WFP costs for all r, but similar

cost when r = 10 km

Comparison of the stakeholder costs obtained with the cost model and the coverage model with 156 FDPs

Conclusions

Defined a framework to optimize food aid distribution networks (FDP locations)

Highlighted the importance of valuing the beneficiaries’ time

Found transportation costs to be the largest costs

Found that, taking beneficiary opportunity costs into account, a relatively low value of r minimizes total costs

Next steps:

How to design food aid supply chains that will lead to a more sustainable response and favour long-term economic growth?

Emerging aid systems Sustainable food security and resilient supply chains

« Cash and Vouchers »

Cash transfers provide money to people who are struggling to

provide food to their families

Vouchers can be redeemed for food items or « spent » in selected

shops

« Local purchase »

WFP purchases locally in developing countries in its criteria of price,

quality and quantity can be met

« Purchase for Progress »

Test new procurement approaches best suited for small producers

Support farmers to get better yields, reduce

losses, improve the quality of their crops and

connect them to markets

Future research

Dynamic and stochastic problem at the national level

Procurement: International

Local

Two type of commodities

Food

Cash & vouchers

Effect on local markets and food production

Stakeholders WFP and Kenya Red Cross

Beneficiaries

Local producers and traders

Non beneficiaries

Discussion

Questions and discussion…